AI agent teams work better when you treat them like emotionally intelligent humans – understanding each agent’s strengths, managing their cognitive load, and letting them collaborate naturally.
The story
I’ve been thinking about how to build better AI agent teams, and realized something weird: emotional intelligence principles actually map perfectly to multi-agent systems.
Stay with me here.
When you’re orchestrating multiple agents – like a Planner, Executor, Verifier, Generator – you’re basically assembling a team with complementary strengths. The Planner needs strategic awareness. The Executor needs focus and reliability. The Verifier needs critical judgment. Sound familiar?
Here’s what I’ve learned the hard way: effective prompting is empathetic communication. You need to understand what each agent is designed to do and frame requests accordingly. Breaking problems into chunks isn’t just good engineering – it’s emotional awareness applied to workflow design. You’re recognizing cognitive load and distributing it thoughtfully.
The really interesting part? Agent communication architectures mirror emotionally intelligent team dynamics. When agents use message passing and maintain autonomy while staying responsive to others’ needs, they’re demonstrating something close to regulation. An agent that backs off when idle and ramps up under pressure shows the kind of adaptive behavior that prevents burnout in human teams.
I’m calling this approach “vibe coding” – designing systems where agents operate authentically within their constraints rather than forcing them into rigid patterns. It means:
– Recognizing each agent’s actual strengths – Managing cognitive load so nothing gets overwhelmed – Creating space for genuine collaboration – Staying aware of how the team perform
Recent Comments